There are conventionally known stereo image processing apparatuses that compute, based on two images (a target image and a reference image) of the same object as captured by a stereo camera, the disparity between those images, and that measure the distance to the object based on the computed disparity between the images. Applications considered for these stereo image processing apparatuses include, for example, an apparatus that measures the distance to a vehicle or pedestrian ahead based on stereo images of the vehicle or pedestrian taken by a vehicle-mounted camera. However, due to the reduction in the sizes of cameras (e.g., vehicle-mounted cameras) in recent years, camera separations are also becoming smaller, as a result of which disparities between stereo images are also becoming smaller. Accordingly, accurate disparity computation functionality is beginning to be demanded of stereo image processing apparatuses.
As an accurate stereo matching (disparity computation in stereo image processing) scheme for stereo image processing apparatuses, a one-dimensional phase only correlation (POC) scheme has been proposed, for example (see Patent Literature 1, for example). In this one-dimensional POC scheme, a partial image (a one-dimensional image data sequence) is first extracted from each of a target image and a reference image using the Hanning window. Next, the extracted partial target image and partial reference image undergo a one-dimensional Fourier transform to be turned into Fourier image data, and are subsequently combined. The amplitude components of the combined Fourier image data are normalized, after which a one-dimensional inverse Fourier transform is performed. A phase-only correlation coefficients are thus derived. The disparity between the images (parallax) is then computed based on the correlation peak of the phase-only correlation coefficients.